Method and apparatus for estimating a maximum time interval error in a data transmission network

ABSTRACT

A method for use in connection with a data transmission network includes receiving a plurality of time interval error data samples over a sampling period and comparing a duration of the sampling period to a time threshold for the sampling period. If the duration of the sampling period is less than or equal to the time threshold for the sampling period, the method includes processing the received plurality of data samples so as to calculate in real time a maximum time interval error. However, if the duration of the sampling period exceeds the time threshold for the sampling period, the method includes dividing the sampling period into a finite number of sub-intervals and processing the data samples in each sub-interval so as to produce a respective intermediate result for each sub-interval. Each of these intermediate results is stored directly after it is produced, and these stored intermediate results are processed so as to estimate the maximum time interval error.

TECHNICAL FIELD OF THE INVENTION

The present invention relates to methods and devices for estimating amaximum time interval error in a data transmission network. Moreparticularly, the present invention relates methods and devices forreal-time estimation of the maximum time interval error for arbitrarytime periods, particularly in systems with low memory capacity.

BACKGROUND OF THE INVENTION

Broadband services such as broadcast TV, video on demand (VoD),telecommunication systems, or the Internet have played an increasinglyimportant role. As a result, in order to obtain a lower cost-per-biteffective transport of signals, in particular data to be transported, anew generation of data transmission network technology has beendeveloped.

New generation data transmission networks demand a high degree ofsynchronization between network transmission elements. Here, animportant factor for all network transmission elements is the timing ofthe network transmission elements. In particular, phase variations inreference clock frequencies governing synchronous network elements mayintroduce errors at various stages in the network.

One measure of timing errors in synchronous data transmission networksis known as the maximum time interval error (MTIE) and is derived from aplurality of time interval error values. A time interval error (TIE)value is defined as the difference between an actual clock and thereference clock, and for any given sampling period, the maximum timeinterval error is defined as the maximum peak-to-peak difference of timeinterval error values within this sampling period.

US 2009/0161744 A1 discloses a method for estimating a maximum timeinterval error in a data transmission network, using information derivedfrom timing pseudowire or packed data flows.

However, implementing directly the definition of the maximum timeinterval error does not permit real-time estimation and, therefore, areal-time display of the results. In particular, the maximum timeinterval error is generally required to be estimated in parallel for aset of different sampling periods, to reveal information about the timevarying behavior of a signal, and aid in the diagnosis of faults. Thesesampling periods typically range from one second up to a day or more.Obtaining the results for such periods conventionally requires a largequantity of data to be collected and, thus, even for the shortestsampling period, the maximum time interval error cannot be calculateduntil the entire dataset has been gathered.

Further, there is a large amount of storage capacity and computing timerequired to obtain the estimated values of the maximum time intervalerror, particularly for long sampling periods.

SUMMARY OF THE INVENTION

It is an object of the present invention to provide improved methods anddevices for estimating a maximum time interval error, particularly forlong sampling periods.

In one embodiment, a method for estimating a maximum time interval errorin a data transmission network comprises receiving a plurality of datasamples over a sampling period and comparing a duration of the samplingperiod to a time threshold for the sampling period. If the duration ofthe sampling period is less than or equal to the time threshold for thesampling period, the received plurality of data samples is processed soas to calculate in real-time a maximum time interval error. Further, ifthe duration of the sampling period exceeds the time threshold for thesampling period, the sampling period is divided into a finite number ofsub-intervals, the data samples received in a first sub-interval areprocessed so as to produce a first intermediate result and theprocessing is successively repeated for successive sub-intervals so asto generate a series of intermediate results. Each element of the seriesof intermediate results is stored directly after the element is producedso as to generate a series of actual stored intermediate results, andthe series of actual stored intermediate results is processed so as toestimate the maximum time interval error.

Thus, if the duration of the sampling period exceeds the time thresholdfor the sampling period (if the sampling period is denoted as a longsampling period) intermediate results produced for successivesub-intervals are stored, rather than the plurality of data samples.Therefore, the size of the stored data and, thus the required storagecapacity, can be reduced while ensuring that the entire plurality ofdata samples received within the sampling period is accounted for.Furthermore, an actual value for the maximum time interval error isestimated from actual stored data, in particular from the series ofactual stored intermediate results and, therefore, before the entireplurality of data samples is gathered. Thus, for long sampling periods,required storage capacity and computing time can be reducedsignificantly compared to conventional methods for estimating themaximum time interval error, without a significant loss of precision.Further, if the duration of the sampling period is less than or equal tothe time threshold for the sampling period, thus if the sampling periodis denoted as a short or medium length sampling period, the maximum timeinterval error can be calculated in real-time by directly processing theplurality of data samples and, therefore, precisely, since less storagecapacity and less time for gathering the plurality of data samples isrequired compared to long sampling periods.

Since the estimation of the maximum time interval error is independentof the estimation of the maximum time interval error for a furtherperiod, the time threshold for the sampling period can be arbitrarilyselected by a user of the data transmission network, for examplecorresponding to the system properties of the data transmission network.

For long sampling periods, the plurality of data samples can be forexample accumulated in bins of 1% of the duration of the sampling periodand thus, the finite number of sub-intervals can be 100.

Further, it should be noted that in this context real-time does notimply that the maximum time interval error is available without anydelay or must be strictly synchronized with the flow of the receivedplurality of data samples. Real-time in this context rather denotes thatthe received plurality of data samples can be processed substantially atthe rate at which the data samples are generated and, thus, gathered.

The plurality of data samples include time interval error values withrespect to a synchronization reference of the data transmission network.Most known methods for estimating a maximum time interval error in adata transmission network are based on those time interval errors and,thus, can be used here without requiring additional effort orappropriate adaptions.

Further, a peak detection function can be used to estimate and/or tocalculate the maximum time interval error. Herein, a peak detectionfunction denotes a function for locating and measuring the peaks intime-series signals. Since the maximum time interval error is defined asthe maximum peak-to-peak difference of time interval error values withina sampling period, such a peak detection function can be used forestimating the maximum time interval error, without requiring additionaleffort or appropriate adaptions.

According to one embodiment, each element of the series of intermediateresults includes a minimum value and a maximum value among the datasamples received over the corresponding sub-interval. This form ofintermediate result is convenient since the maximum time interval erroris defined as the maximum peak-to-peak difference of time interval errorvalues and, therefore, the difference of a minimum value among the timeinterval error values and a maximum value among the time interval errorvalues. Thus, required storage capacity and computing time can befurther reduced.

Each of the minimum values among the received data samples over thecorresponding sub-interval can be stored in a first list, each of themaximum values among the received data samples over the correspondingsub-interval can be stored in a second list and the maximum timeinterval error can be estimated from a minimal value among the elementsstored in the first list and a maximum value among the elements storedin the second list. Since the maximum time interval error usuallycorresponds to the difference between the minimal value among theelements stored in the first list and the maximum value among theelements stored in the second list, the maximum time interval error canbe produced with only a small number of samples of the plurality of datasamples requiring examination.

According to a further embodiment, the step of processing the datasamples so as to calculate in real-time a maximum time interval error ifthe duration of the sampling period is less than or equal to the timethreshold for the sampling period further comprises comparing a quantityof the plurality of data samples received over the sampling period to athreshold value for the quantity of data samples. If the quantity of theplurality of data samples received over the sampling period is less thanor equal to the threshold value for the quantity of data samples, theplurality of data samples received over the sampling period are directlystored and the maximum time interval error is calculated from the storedplurality of data samples. If the quantity of the plurality of datasamples received over the sampling period exceeds the threshold valuefor the quantity of data samples, a tree data structure is created onthe basis of the plurality of data samples received over the samplingperiod, the tree data structure is stored and the maximum time intervalerror is calculated from the stored tree data structure. The thresholdvalue for the quantity of data samples may correspond to an availablestorage capacity.

Thus, if the duration of the sampling period is less than or equal tothe time threshold value for the sampling period, it can be furtherdistinguished whether the sampling period is a short or a medium lengthperiod based on the quantity of data samples collected. If the samplingperiod is denoted as a short period, there is enough storage capacity todirectly store the plurality of data samples received over the samplingperiod, and, therefore, the maximum time interval error can be easilycalculated in real-time from the stored plurality of data samples. Ifthe sampling period is denoted as a medium length period, there is notenough storage capacity to directly store each of the plurality of datasamples received over the sampling period. However, a tree datastructure can be created on the basis of the plurality of data samplesreceived over the sampling period, the tree data structure can be storedand the maximum time interval error can be calculated from the storedtree data structure by using a tree algorithm. Since tree algorithms areknown in the art and are fast algorithms, the maximum time intervalerror can be calculated in real-time for medium length periods, too,without requiring additional effort or appropriate adaptions. As used inthis disclosure and the accompanying claims a tree data structure is anon-linear data structure having a root node and potentially many levelsof additional nodes, for example defined by the received data samplesthat form a hierarchy, for example describing a difference betweensuccessive data samples of the plurality of data samples.

Further, the method can comprise the steps of comparing the estimatedand/or the calculated maximum time interval error to a predefined limitfor the maximum time interval error and generating a warning signal forthe user of the data transmission network if the estimated and/or thecalculated maximum time interval error exceeds the predefined limit forthe maximum time interval error. The warning signal is preferablydisplayed on a display unit of the data transmission network.

Since the maximum time interval error can be used to detect clockinstability that can cause data loss on a communication channel withinthe data transmission network, the maximum time interval error can beused to evaluate the performance of equipment and system. Thus, bygenerating a warning signal for the user of the data transmissionnetwork, if the estimated and/or the calculated maximum time intervalerror exceeds the predefined limit for the maximum time interval error,the user can be informed that a fault, which might impair customerservice, has been diagnosed.

An apparatus according to the present invention for estimating a maximumtime interval error in a data transmission network may comprise inputmeans for receiving a plurality of data samples over a sampling periodand a processing means for estimating a maximum time interval error. Theprocessing means may comprise a first comparing means for comparing aduration of the sampling period to a time threshold for the samplingperiod, a first calculating means for processing the received pluralityof data samples so as to calculate in real-time a maximum time intervalerror if the duration of the sampling period is less than or equal tothe time threshold for the sampling period, and a second calculatingmeans for processing the received plurality of data samples so as toestimate the maximum time interval error if the duration of the samplingperiod exceeds the time threshold for the sampling period. The secondcalculating means may comprise a dividing means for dividing thesampling period into a finite number of sub-intervals, a thirdcalculating means for processing data samples received in a firstsub-interval of the sampling period so as to produce a firstintermediate result and successively repeating the processing forsuccessive sub-intervals so as to generate a series of intermediateresults, a first storing means for storing each element of the series ofintermediate results directly after the element is produced so as togenerate a series of actual stored intermediate results and a fourthcalculating means for processing the series of actual storedintermediate results so as to estimate the maximum time interval error.

Thus the apparatus includes a processing means for estimating a maximumtime interval error, wherein the processing means is adapted to storeintermediate results produced for successive sub-intervals rather thanthe plurality of data samples if the duration of the sampling periodexceeds the time threshold for the sampling period, thus if the samplingperiod is denoted as a long sampling period. Therefore, the size of thestored data and, therefore, the required storage capacity within theapparatus can be reduced, while ensuring that the entire plurality ofdata samples within the sampling period is accounted for. Furthermore,the fourth calculating means is adapted to estimate an actual value forthe maximum time interval error from actual stored data, in particularfrom the series of actual stored intermediate results and, therefore,before the entire plurality of data samples is gathered. Thus, for longsampling periods, required storage capacity and computing time can besignificantly reduced compared to conventional apparatuses forestimating the maximum time interval error, without a significant lossof precision when estimating the maximum time interval error. Further,the processing means is adapted to calculate the maximum time intervalerror in real-time by directly processing the plurality of data samplesand, therefore, precisely, if the duration of the sampling period isless than or equal to the time threshold for the sampling period, thusif the sampling period is denoted as a short or medium length samplingperiod, since less storage capacity and less time for gathering theplurality of data samples is required compared to long sampling periods.

Since, in an apparatus according to the invention, the estimation of themaximum time interval error is independent of the estimation of themaximum time interval error for a further period, the time threshold forthe sampling period can be arbitrarily selected by a user of the datatransmission. For example, the time threshold for the sampling periodmay be selected to correspond to the system properties of the datatransmission network. Thus the apparatus may include further input meansfor allowing a user of the data transmission network to selectivelyinput the time threshold for the sampling period.

For long sampling periods, the dividing means can for example accumulatethe plurality of data samples in bins of 1% of the duration of thesampling period and thus, the finite number of sub-intervals can be 100.

Further, it should be noted that in this context real-time does notimply that the maximum time interval error is available without anydelay or must be strictly synchronized with the flow of the receivedplurality of data samples. Real-time in this context rather denotes thatthe received plurality of data samples can be processed substantially atthe rate at which the data samples are generated and, thus, gathered.

The plurality of data samples include time interval error values withrespect to a synchronization reference of the data transmission network.Most known apparatuses for estimating a maximum time interval error in adata transmission network are based on methods using those time intervalerrors, which, thus, can be used without requiring additional effort orappropriate adaptions to the apparatus.

Further, the first calculating means and/or the fourth calculating meanscan use a peak detection algorithm stored in the processing means, toestimate and/or to calculate the maximum time interval error. As used inthis disclosure, a peak detection function denotes a function forlocating and measuring the peaks in time-series signals. Since themaximum time interval error is defined as the maximum peak-to-peakdifference of time interval error values within a sampling period,program code for such a peak detection function can be stored and usedfor estimating the maximum time interval error, without requiringadditional effort or appropriate adaptions.

In some embodiments, each element of the series of intermediate resultsmay include a minimum value and a maximum value among the data samplesreceived over the corresponding sub-interval since, as noted above, themaximum time interval error is defined as the maximum peak-to-peakdifference of time interval error values (that is, the difference of aminimum value among the time interval error values and a maximum valueamong the time interval error values). Thus, required storage capacitywithin the apparatus and computing time can be further reduced.

Each of the minimum values among the data samples received over acorresponding sub-interval can be stored by the first storing means in afirst list, each of the maximum values among the data samples receivedover a corresponding sub-interval can be stored by the first storingmeans in a second list, and the fourth calculating means can use aminimal value among the elements stored in the first list and a maximumvalue among the elements stored in the second list to estimate themaximum time interval error. Since the maximum time interval errorusually corresponds to the difference between the minimal value amongthe elements stored in the first list and the maximum value among theelements stored in the second list, the fourth calculating means thusmay be configured to produce the maximum time interval error with only asmall number of samples of the plurality of data samples requiringexamination.

In some embodiments, the first calculating means comprises a secondcomparing means for comparing a quantity of the plurality of datasamples received over the sampling period to a threshold value for thequantity of data samples and a fifth calculating means for calculatingthe maximum time interval error if the quantity of the plurality of datasamples received over the sampling period is less than or equal to thethreshold value for the quantity of data samples. The fifth calculatingmeans may include a second storing means for directly storing theplurality of data samples received over the sampling period and a sixthcalculating means for calculating the maximum time interval error fromthe stored plurality of data samples. The first calculating means mayfurther include a seventh calculating means for calculating the maximumtime interval if the quantity of the plurality of data samples receivedover the sampling period exceeds the threshold value for the quantity ofdata samples. This seventh calculating means may include a creatingmeans for creating a tree data structure on the basis of the pluralityof data samples received over the sampling period, a third storing meansfor storing the tree data structure, and an eighth calculating means forcalculating the maximum time interval error from the stored tree datastructure. In this embodiment, the threshold value for the quantity ofdata samples may correspond to an available storage capacity within theapparatus.

With this first calculating means configuration, if the duration of thesampling period is less than or equal to the time threshold value forthe sampling period, the first calculating means can further distinguishwhether the sampling period is a short or a medium length period. If thesampling period is denoted as a short period, there is enough storagecapacity within the apparatus to directly store the plurality of datasamples received over the sampling period, and, therefore, the maximumtime interval error can be easily calculated in real-time from thestored plurality of data samples. If the sampling period is denoted as amedium length period, there is not enough storage capacity within theapparatus to directly store each of the plurality of data samplesreceived over the sampling period. However, a tree data structure can becreated by the creating means on the basis of the plurality of datasamples received over the sampling period, the tree data structure canbe stored and the maximum time interval error can be calculated from thestored tree data structure by using a tree algorithm stored in theprocessing means. Since tree algorithms are known in the art and arefast algorithms, such an algorithm can be implemented in the processingmeans without requiring additional effort or appropriate adaptions andthe maximum time interval error can be calculated in real-time formedium length periods, too. Here, a tree is a non-linear data structurehaving a root node and potentially many levels of additional nodes, forexample defined by the received data samples that form a hierarchy, forexample describing a difference between successive data samples of theplurality of data samples.

The invention further encompasses a data transmission network whichincludes an estimating apparatus as described above. In such a datatransmission network, if the duration of the sampling period exceeds thetime threshold for the sampling period, thus is denoted as a longsampling period, intermediate results produced for successivesub-intervals are stored, rather than the plurality of data samples and,therefore, the size of the stored data and, therefore, the requiredstorage capacity can be reduced, while ensuring that the entireplurality of data samples within the sampling periods is accounted for.Furthermore, an actual value for the maximum time interval error isestimated from actual stored data, in particular from the series ofactual stored intermediate results and, therefore, before the entireplurality of data samples is gathered. Thus, for long sampling periods,required storage capacity and computing time can be significantlyreduced compared to conventional methods for estimating the maximum timeinterval error, without a significant loss of precision. Further, if theduration of the sampling period is less than or equal to the timethreshold for the sampling period, thus if the sampling period isdenoted as a short or medium length sampling period, the maximum timeinterval error can be calculated in real-time by directly processing theplurality of data samples and, therefore, precisely, since less storagecapacity and less time for gathering the plurality of data samples isrequired compared to long sampling periods.

The data transmission network may further include a third comparingmeans for comparing the estimated and/or the calculated maximum timeinterval error to a predefined limit for the maximum time interval errorand a warning means for generating a warning signal for a user of thedata transmission network if the estimated and/or the calculated maximumtime interval error exceeds the predefined limit for the maximum timeinterval error. The warning signal is preferably displayed on a displayunit of the data transmission network.

Since the maximum time interval error can be used to detect clockinstability that can cause data loss on a communication channel withinthe data transmission network, the maximum time interval error can beused to evaluate the performance of equipment and system. Thus, bygenerating a warning signal for the user of the data transmissionnetwork, if the estimated time interval error exceeds the predefinedlimit for the maximum time interval error, the user can be informed thata fault, which might impair customer service, has been diagnosed.

These and other advantages and features of the invention will beapparent from the following description of illustrative embodiments,considered along with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a data transmission network in whichembodiments of the present invention may be implemented.

FIG. 2 is a block diagram of an apparatus for estimating a maximum timeinterval error according to a first embodiment of the present invention.

FIG. 3 is a flow chart of a method for estimating a maximum timeinterval error in a data transmission network according to an embodimentof the invention.

FIG. 4 is a flow chart showing another aspect of the present inventionwhich varies the storage of data samples and calculating a maximum timeinterval error depending upon the quantity of data samples.

DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

As shown in FIG. 1 a data transmission network 1 in which the presentinvention may be implemented may include a transport network 2 includingat least one transport node 3. Generally, larger networks include aplurality of transport nodes, which can be realized for example byrouters or switches. Here, at a central time information distributionnode 4, a digital timing signal, including the central time informationfor at least one of the timing parameters absolute time, relative time,frequency and phase is transmitted into the transport network 2.Further, the network 1 includes at least one, usually a plurality, ofreceiving nodes 5 at which the digital timing signal including thecentral time information is received and processed in order tosynchronize the timing at the receiving node 5 and the time informationat the central time information distribution node 4. This informationcan, for example, be used to affect a clock recovery so that one or moresignals created at the receiving node are transmitted according to aprescribed timing pattern.

One measure of timing errors in synchronous data transmission networksis known as the maximum time interval error (MTIE) and is derived from aplurality of time interval error values. Here, a time interval error(TIE) value is defined as the difference between an actual clock and thereference clock, and for any given sampling period, the maximum timeinterval error is defined as the maximum peak-to-peak difference of timeinterval error values within this sampling period.

However, implementing directly the definition of the maximum timeinterval error does not permit real-time estimation and, therefore, areal-time display of the results. In particular, the maximum timeinterval error is generally required to be estimated in parallel for aset of different sampling periods, to reveal information about the timevarying behavior of a signal, and aid in the diagnosis of faults. Thesesampling periods typically range from one second up to a day or more.Obtaining the results for such periods conventionally requires a largequantity of data to be collected and, thus, even for the shortestsampling period, the maximum time interval error cannot be calculateduntil the entire dataset has been gathered.

Further, there is a large amount of storage capacity and computing timerequired to obtain the estimated values of the maximum time intervalerror, particularly for long sampling periods.

FIG. 2 illustrates a block diagram of an apparatus 10 for estimating amaximum time interval error in a data transmission network according toa first embodiment. The illustrated apparatus 10 comprises an inputmeans 11 for receiving a plurality of data samples over a samplingperiod and a processing means 12 for estimating a maximum time intervalerror. Apparatus 10 may be included at any suitable point in datatransmission network 1 (FIG. 1) for receiving data samples via inputmeans 11. Processing means 12 may comprise a suitable general or specialpurpose processing device adapted to receive data samples from inputmeans 11 and to implement the various comparing means, calculatingmeans, storing means, creating means, and dividing means describedfurther below in reference to the figures.

The processing means 12 comprises a first comparing means 13 forcomparing a duration of the sampling period to a time threshold for thesampling period, a first calculating means 14 for processing thereceived plurality of data samples so as to calculate in real-time themaximum time interval error if the duration of the sampling period isless than or equal to the time threshold for the sampling period, and asecond calculating means 15 for processing the received plurality ofdata samples so as to estimate the maximum time interval error if theduration of the sampling period exceeds the time threshold for thesampling period. As can be seen in FIG. 2, the second calculating means15 comprises a dividing means 16 for dividing the sampling period into afinite number of sub-intervals, a third calculating means 17 forprocessing the data samples received over a first sub-interval of thesampling period so as to produce a first intermediate result andsuccessively repeating the processing for successive sub-intervals so asto generate a series of intermediate results, a first storing means 18for storing each element of the series of intermediate results directlyafter the element is produced so as to generate a series of actualstored intermediate results, and a fourth calculating means 19 forprocessing the series of actual stored intermediate results so as toestimate the maximum time interval error.

Thus, the apparatus 10 according to FIG. 2 comprises a processing means12 for estimating a maximum time interval error, wherein the processingmeans 12 is adapted to store intermediate results produced forsuccessive sub-intervals rather than the plurality of data samples ifthe duration of the sampling period exceeds the time threshold for thesampling period, thus if the sampling period is denoted as a longsampling period. Therefore, the size of the stored data and, therefore,the required storage capacity within the apparatus 10 can be reduced,while ensuring that the entire plurality of data samples within thesampling periods is accounted for. Furthermore, the fourth calculatingmeans 19 is accomplished to estimate an actual value for the maximumtime interval error from actual stored data, in particular from theseries of actual stored intermediate results and, therefore, before theentire plurality of data samples is gathered. Further, the processingmeans 12 is adapted to calculate the maximum time interval error inreal-time by directly processing the plurality of data samples and,therefore, precisely, if the duration of the sampling period is lessthan or equal to the time threshold for the sampling period, thus if thesampling period is denoted as a short or medium length sampling period,since less storage capacity and less time for gathering the plurality ofdata samples is required compared to long sampling periods.

Since, in the apparatus 10 according to the invention, the estimation ofthe maximum time interval error is independent of the estimation of themaximum time interval error for a further period, the time threshold forthe sampling period can be arbitrarily selected by a user of the datatransmission, for example corresponding to the system properties of thedata transmission network.

For long sampling periods in some implementations of the invention, thedividing means 16 accumulates the plurality of data samples in bins of1% of the duration of the sampling period and thus, the finite number ofsub-intervals is 100.

Further, it should be noted that in this context real-time does notimply that the maximum time interval error is available without anydelay or must be strictly synchronized with the flow of the receivedplurality of data samples. Real-time in this context rather denotes thatthe received plurality of data samples can be processed substantially atthe rate at which the data samples are generated and, thus, gathered.

According to the embodiment shown in FIG. 2, the plurality of datasamples received at the input means 11 include time interval errorvalues with respect to a synchronization of the data transmissionnetwork.

Further, the first calculating means 14 and the fourth calculating means19 use a peak detection algorithm to estimate and/or calculate themaximum time interval error, wherein a code (program code) of the peakdetection algorithm is stored in the processing means 12 and executed bythe first calculating means 14 and the fourth calculating means 19.

According to the embodiment shown in FIG. 2, each element of the seriesof intermediate results includes a minimum value and a maximum valueamong the data samples received over the corresponding sub-interval.

Each of the minimum values among the data samples received over acorresponding sub-interval may be stored by the first storing means 18in a first list, and each of the maximum values among the data samplesreceived over a corresponding sub-interval may be stored by the firststoring means 18 in a second list. The fourth calculating means 19 thenuses a minimum value among the elements stored in the first list and amaximum value among the elements stored in the second list to estimatethe maximum time interval error.

As shown in FIG. 2, the first calculating means 14 further comprises asecond comparing means 20 for comparing a quantity of the plurality ofdata samples received over the sampling period to a threshold value forthe quantity of data samples. There is further shown a fifth calculating21 means for calculating the maximum time interval error if the quantityof the plurality of data samples is less than or equal to the thresholdvalue for the quantity of data samples, which comprises a second storingmeans 22 for directly storing the plurality of data samples receivedover the sampling period and a sixth calculating means 23 forcalculating the maximum time interval error from the stored plurality ofdata samples. There is also shown a seventh calculating means 24 forcalculating the maximum time interval error if the quantity of theplurality of data samples exceeds the threshold value for the quantityof data samples, which comprises a creating means 25 for creating a treedata structure on the basis of the plurality of data samples receivedover the sampling period, a third storing means 26 for storing the treedata structure, and an eighth calculating means 27 for calculating themaximum time interval error from the stored tree data structure. In theembodiment shown in FIG. 2, the threshold value for the quantity of datasamples may correspond to an available storage capacity within theapparatus 10.

Thus, if the duration of the sampling period is less than or equal tothe time threshold value for the sampling period, the first calculatingmeans 14 can further distinguish whether the sampling period is a shortor a medium length period. If the sampling period is denoted as a shortperiod, there is enough storage capacity within the apparatus 10 todirectly store the plurality of data samples received over the samplingperiod, and, therefore, the maximum time interval error can be easilycalculated in real-time from the stored plurality of data samples. Ifthe sampling period is denoted as a medium length period, there is notenough storage capacity within the apparatus 10 to directly store eachof the plurality of data samples received over the sampling period.However, a tree data structure can be created by the creating means 25on the basis of the plurality of data samples received over the samplingperiod, the tree data structure can be stored and the maximum timeinterval error can be calculated from the stored tree data structure byusing a tree algorithm stored in the processing means. Since treealgorithms are known in the art and are fast algorithms, such analgorithm can be implemented in the processing means 12 withoutrequiring additional effort or appropriate adaptions and the maximumtime interval error can be calculated in real-time for medium lengthperiods, too. Herein, a tree is a non-linear data structure having aroot node and potentially many levels of additional nodes, for exampledefined by the received data samples that form a hierarchy, for exampledescribing a difference between successive data samples of the pluralityof data samples.

FIG. 3 illustrates a flow chart of a method 30 for estimating a maximumtime interval error in a data transmission network according to a secondembodiment. In this embodiment, the method 30 begins at step 31, whereina plurality of data samples are received over a sampling period. At afollowing step 32, a duration of the sampling period is compared to atime threshold for the sampling period. If the duration of the samplingperiod is less than or equal to the time threshold for the samplingperiod, the received plurality of data samples are processed at step 33so as to calculate in real-time a maximum time interval error. However,if the duration of the sampling period exceeds the time threshold forthe sampling period, the maximum time interval error is estimated atstep 34 by dividing the sampling period into a finite number ofsub-intervals, processing the data samples received over a firstsub-interval so as to produce a first intermediate result andsuccessively repeating the processing for successive sub-intervals so asto generate a series of intermediate results, storing each element ofthe series of intermediate results directly after the element isproduced so as to generate a series of actual stored intermediateresults, and processing the series of actual stored intermediate resultsso as to estimate the maximum time interval error.

Thus, according to the method, if the duration of the sampling periodexceeds the time threshold for the sampling period, thus if the samplingperiod is denoted as a long sampling period, intermediate resultsproduced for successive sub-intervals are stored, rather than theplurality of data samples and, therefore, the size of the stored dataand, therefore, the required storage capacity can be reduced, whileensuring that the entire plurality of data samples received within thesampling period is accounted for. Furthermore, an actual value for themaximum time interval error is estimated from actual stored data, inparticular from the series of actual stored intermediate results and,therefore, before the entire plurality of data samples is gathered.Further, if the duration of the sampling period is less than or equal tothe time threshold for the sampling period, thus if the sampling periodis denoted as a short or medium length sampling period, the maximum timeinterval error can be calculated in real-time by directly processing theplurality of data samples and, therefore, precisely, since less storagecapacity and less time for gathering the plurality of data samples isrequired compared to long sampling periods.

Since the estimation of the maximum time interval error is independentof the estimation of the maximum time interval error for a furtherperiod, the time threshold for the sampling period can be arbitrarilyselected by a user of the data transmission network, for examplecorresponding to the system properties of the data transmission network.For long sampling periods, the plurality of data samples may, forexample, be accumulated in bins of 1% of the duration of the samplingperiod and thus, the finite number of sub-intervals may be 100.

Further, it should be noted that in this context real-time does notimply that the maximum time interval error is available without anydelay or must be strictly synchronized with the flow of the receivedplurality of data samples. Real-time in this context rather denotes thatthe received plurality of data samples can be processed substantially atthe rate at which the data samples are generated and, thus, gathered.

According to the embodiment shown in FIG. 3, the plurality of datasamples include time interval error samples with respect to asynchronization reference of the data transmission network.

Further, a peak detection function is used to estimate the maximum timeinterval error.

According to the embodiment shown in FIG. 3, each element of the seriesof intermediate results includes a minimum value and a maximum valueamong the data samples received over the corresponding sub-interval.

Here, each of the minimum values among the data samples received over acorresponding sub-interval is stored in a first list, each of themaximum values among the data samples received over a correspondingsub-interval is stored in a second list and the maximum time intervalerror is estimated from a minimum value among the elements stored in thefirst list and a maximum value among the elements stored in the secondlist.

FIG. 3 further shows the step 35 of comparing the estimated maximum timeinterval error and/or the calculated maximum time interval error to apredefined limit for the maximum time interval error, and the step 36 ofgenerating a warning signal for a user of the data transmission networkif the estimated time interval error exceeds the predefined limit forthe maximum time interval error. According to the embodiment of FIG. 3,the warning signal is displayed on a display unit of the datatransmission network.

Since the maximum time interval error can be used to detect clockinstability that can cause data loss on a communication channel withinthe data transmission network, the maximum time interval error can beused to evaluate the performance of equipment and system. Thus, bygenerating a warning signal for the user of the data transmissionnetwork, if the estimated time interval error exceeds the predefinedlimit for the maximum time interval error, the user can be informed thata fault, which might impair customer service, has been diagnosed.

FIG. 4 illustrates processing the received plurality of data samples soas to calculate in real-time the maximum time interval error if theduration of the sampling period is less than or equal to the timethreshold for the sampling period, according to a third embodiment.

According to the embodiment shown in FIG. 4, processing the receivedplurality of data samples so as to calculate in real-time the maximumtime interval error if the duration of the sampling period is less thanor equal to the time threshold for the sampling period comprises thestep 40 of comparing a quantity of the plurality of data samplesreceived over the sampling period to a threshold value for the quantityof data samples.

There is further shown the step 41 of directly storing the plurality ofdata samples received over the sampling period and calculating themaximum time interval error from the stored plurality of data samples ifthe quantity of data samples received over the sampling period is lessthan or equal to the threshold value for the quantity of data samples.

If the quantity of the plurality of data samples exceeds the thresholdvalue for the quantity of data samples received over the samplingperiod, at step 42 a tree data structure is created on the basis of theplurality of data samples received over the sampling period, the treedata structure is stored and the maximum time interval error isestimated from the stored tree data structure. According to theembodiment shown in FIG. 4, the threshold value for the quantity of datasamples corresponds to an available storage capacity.

Thus, if the duration of the sampling period is less than or equal tothe time threshold value for the sampling period, it can be furtherdistinguished whether the sampling period is a short or a medium lengthperiod. If the sampling period is denoted as a short period, there isenough storage capacity to directly store the plurality of data samplesreceived over the sampling period, and, therefore, the maximum timeinterval error can be easily calculated in real-time from the storedplurality of data samples. If the sampling period is denoted as a mediumlength period, there is not enough storage capacity to directly storeeach of the plurality of data samples received over the sampling period.However, a tree data structure can be created on the basis of theplurality of data samples received over the sampling period, the treedata structure can be stored and the maximum time interval error can becalculated from the stored tree data structure by using a treealgorithm. Since tree algorithms are known in the art and are fastalgorithms, the maximum time interval error can be calculated inreal-time for medium length periods, too, without requiring additionaleffort or appropriate adaptions. Herein, a tree is a non-linear datastructure having a root node and potentially many levels of additionalnodes, for example defined by the received data samples that form ahierarchy, for example describing a difference between successive datasamples of the plurality of data samples.

As used herein, whether in the above description or the followingclaims, the terms “comprising,” “including,” “carrying,” “having,”“containing,” “involving,” and the like are to be understood to beopen-ended, that is, to mean including but not limited to. Any use ofordinal terms such as “first,” “second,” “third,” etc., in the claims tomodify a claim element does not by itself connote any priority,precedence, or order of one claim element over another, or the temporalorder in which acts of a method are performed. Rather, unlessspecifically stated otherwise, such ordinal terms are used merely aslabels to distinguish one claim element having a certain name fromanother element having a same name (but for use of the ordinal term).

The above described preferred embodiments are intended to illustrate theprinciples of the invention, but not to limit the scope of theinvention. Various other embodiments and modifications to thesepreferred embodiments may be made by those skilled in the art withoutdeparting from the scope of the present invention.

The invention claimed is:
 1. A method for estimating a maximum timeinterval error in a data transmission network, the method comprising:(a) receiving at a processing device a plurality of data samples fromthe data transmission network over a sampling period; (b) with theprocessing device, comparing a duration of the sampling period to asampling period time threshold; (c) if the duration of the samplingperiod is less than or equal to the sampling period time threshold,processing the plurality of data samples with the processing device soas to calculate in real time a maximum time interval error for thesampling period, wherein processing the plurality of data samples so asto calculate in real time the maximum time interval error includes, (i)comparing a quantity of the plurality of data samples received over thesampling period to a data sample quantity threshold value; (ii) if thequantity of the plurality of data samples received over the samplingperiod is less than or equal to the data sample quantity thresholdvalue, directly storing the plurality of data samples received over thesampling period and calculating the maximum time interval error from thestored plurality of data samples; and (iii) if the quantity of theplurality of data samples received over the sampling period exceeds thedata sample quantity threshold value, creating a tree data structure onthe basis of the plurality of data samples received over the samplingperiod, storing the tree data structure, and calculating the maximumtime interval error from the stored tree data structure; and (d) if theduration of the sampling period exceeds the sampling period timethreshold, dividing the sampling period into a number of sub-intervals,processing the data samples received in each respective sub-intervalwith the processing device to produce a respective intermediate resultfor each respective sub-interval, storing each respective intermediateresult directly after the respective intermediate result is produced,and processing the stored intermediate results with the processingdevice so as to produce a maximum time interval error estimate.
 2. Themethod of claim 1 wherein the data samples each include a time intervalerror value with respect to a synchronization reference of the datatransmission network.
 3. The method of claim 1 further includingapplying a peak detection function in processing the stored intermediateresults so as to produce the maximum time interval error estimate. 4.The method of claim 1 wherein each respective intermediate resultincludes a minimum value and a maximum value among the data samplesreceived over the respective sub-interval corresponding to thatintermediate result.
 5. The method of claim 4 wherein: (a) storing eachrespective intermediate result includes storing the respective minimumvalue included in that intermediate result in a first list, and storingthe respective maximum value included in that intermediate result in asecond list; and (b) the maximum time interval error estimate isproduced from the lowest value among the values stored in the first listand the highest value among the elements stored in the second list. 6.The method of claim 1 wherein data sample quantity threshold valuecorresponds to an available storage capacity of a processing deviceperforming the processing of the plurality of data samples so as tocalculate in real time the maximum time interval error for the samplingperiod.
 7. The method of claim 1 wherein the method further comprises:(a) comparing the maximum time interval error or the maximum timeinterval error estimate to a predefined maximum time interval errorlimit; and (b) if the comparison at element (a) of this claim shows thatthe maximum time interval error limit is exceeded, generating a warningsignal for a user of the data transmission network.
 8. An apparatus forestimating a maximum time interval error in a data transmission network,the apparatus comprising: (a) input means for receiving a plurality ofdata samples over a sampling period; (b) first comparing means forcomparing a duration of the sampling period to a sampling period timethreshold; (c) first calculating means for processing the receivedplurality of data samples so as to calculate in real time a maximum timeinterval error if the duration of the sampling period is less than orequal to the sampling period time threshold; (d) second calculatingmeans for processing the received plurality of data samples if theduration of the sampling period exceeds the sampling period timethreshold, the second calculating means comprising, (i) dividing meansfor dividing the sampling period into a number of sub-intervals, (ii)third calculating means for processing the data samples received in eachrespective sub-interval to produce a respective intermediate result foreach respective sub-interval, (iii) first storing means for storing eachrespective intermediate result directly after the respectiveintermediate result is produced, and (iv) fourth calculating means forprocessing the stored intermediate results so as to produce a maximumtime interval error estimate; and (e) wherein the first calculatingmeans comprises, (i) second comparing means for comparing a quantity ofthe plurality of data samples received over the sampling period to athreshold value for the quantity of data samples; (ii) fifth calculatingmeans for calculating the maximum time interval error if the quantity ofthe plurality of data samples is less than or equal to the thresholdvalue for the quantity of data samples, the fifth calculating meanscomprising, second storing means for directly storing the plurality ofdata samples received over the sampling period, and sixth calculatingmeans for calculating the maximum time interval error from the storedplurality of data samples; and (iii) seventh calculating means forcalculating the maximum time interval error if the quantity of theplurality of data samples exceeds the threshold value for the quantityof data samples, the seventh calculating means comprising, creatingmeans for creating a tree data structure on the basis of the pluralityof data samples received over the sampling period, third storing meansfor storing the tree data structure, and eighth calculating means forcalculating the maximum time interval error from the stored tree datastructure.
 9. The apparatus of claim 8 wherein the data samples eachinclude a time interval error value with respect to a synchronizationreference of the data transmission network.
 10. The apparatus of claim 8wherein the first calculating means applies a peak detection algorithmstored in the apparatus to calculate the maximum time interval error.11. The apparatus of claim 8 wherein the fourth calculating meansapplies a peak detection algorithm stored in the apparatus to productthe maximum time interval estimate.
 12. The apparatus of claim 8 whereineach respective intermediate result includes a minimum value and amaximum value among the data samples received over the respectivesub-interval corresponding to that intermediate result.
 13. Theapparatus of claim 12 wherein: (a) the first storing means stores eachrespective minimum value in a first list and stores each respectivemaximum value in a second list; and (b) the fourth calculating meansselects the lowest value stored in the first list and the highest valuestored in the second list to produce the maximum time interval errorestimate.
 14. A data transmission network comprising: (a) at least onetransport network and at least one transport node; (b) at least onereceiving node; (c) a central time information distribution node; (d)input means for receiving a plurality of data samples over a samplingperiod, each data sample comprising a time interval error value; (e)first comparing means for comparing a duration of the sampling period toa sampling period time threshold; (f) first calculating means forprocessing the received plurality of data samples so as to calculate inreal time a maximum time interval error if the duration of the samplingperiod is less than or equal to the sampling period time threshold; and(g) second calculating means for processing the received plurality ofdata samples if the duration of the sampling period exceeds the samplingperiod time threshold, the second calculating means comprising, (i)dividing means for dividing the sampling period into a number ofsub-intervals, (ii) third calculating means for processing the datasamples received in each respective sub-interval to produce a respectiveintermediate result for each respective sub-interval, (iii) firststoring means for storing each respective intermediate result directlyafter the respective intermediate result is produced, and (iv) fourthcalculating means for processing the stored intermediate results so asto produce a maximum time interval error estimate; and (h) wherein thefirst calculating means comprises, (i) second comparing means forcomparing a quantity of the plurality of data samples received over thesampling period to a threshold value for the quantity of data samples;(ii) fifth calculating means for calculating the maximum time intervalerror if the quantity of the plurality of data samples is less than orequal to the threshold value for the quantity of data samples, the fifthcalculating means comprising, second storing means for directly storingthe plurality of data samples received over the sampling period, andsixth calculating means for calculating the maximum time interval errorfrom the stored plurality of data samples, and (iii) seventh calculatingmeans for calculating the maximum time interval error if the quantity ofthe plurality of data samples exceeds the threshold value for thequantity of data samples, the seventh calculating means comprising,creating means for creating a tree data structure on the basis of theplurality of data samples received over the sampling period, thirdstoring means for storing the tree data structure, and eighthcalculating means for calculating the maximum time interval error fromthe stored tree data structure.
 15. The data transmission network ofclaim 14 wherein each respective intermediate result includes a minimumvalue and a maximum value among the data samples received over therespective sub-interval corresponding to that intermediate result. 16.The data transmission network of claim 15 wherein: (a) the first storingstores each respective minimum value in a first list and stores eachrespective maximum value in a second list; and (b) the fourthcalculating means selects the lowest value stored in the first list andthe highest value stored in the second list to produce the maximum timeinterval error estimate.
 17. The data transmission network of claim 14further including: (a) third comparing means for comparing the maximumtime interval error or the maximum time interval error estimate to apredefined maximum time interval error limit; and (b) warning means forgenerating a warning signal for the user of the data transmissionnetwork if the comparison at element (a) of this claim shows that themaximum time interval error is exceeded.